Monitoring Lake Ice Seasons in Southwest Alaska with Modis Images
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MONITORING LAKE ICE SEASONS IN SOUTHWEST ALASKA WITH MODIS IMAGES Page Spencer, Chief of Natural Resources Lake Clark National Park and Preserve 240 W 5th Ave Anchorage, Alaska 99501 [email protected] Amy E. Miller, Ecologist National Park Service, Southwest Alaska Network 240 W 5th Ave Anchorage, Alaska 99501 [email protected] Bradley Reed. Associate Program Coordinator U.S. Geological Survey (USGS) Reston, VA 20191 [email protected] Michael Budde, Geographer USGS Center for Earth Resources Observation and Science (EROS) Sioux Falls, SD 57198 [email protected] ABSTRACT Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) Rapidfire browse images, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions. The general annual pattern of the lake ice season in southwest Alaska begins as water cools when fall storms sweep in from the North Pacific. Ice forms on high altitude or small lakes by Oct/Nov, with larger lakes usually freezing over by Dec/Jan. Warm mid-winter storms often hit the study area, bringing wind, rain and melting temperatures that result in several inches of water on the ice or partial break-up of the ice pack. The return of cold, still Arctic high pressure refreezes the lakes until spring break-up in April and May. Throughout the observation period (2001–2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area. INTRODUCTION Ecosystem responses to changing climate are expected to occur over different temporal scales, with the timing of seasonal events (e.g., freeze-thaw cycles, snowpack formation and snowmelt, and the onset or end of the growing season) showing a great deal of variability. Long-term changes in snowpack, lake ice, and vegetation may be particularly pronounced in high northern latitudes where small changes in climate can alter the timing of these events. Remotely sensed data can potentially capture much of this variation in seasonality, and provided that the Pecora 17 – The Future of Land Imaging…Going Operational November 18 – 20, 2008 Denver, Colorado data record is sufficiently long, enable us to distinguish between interannual variability and multi-year trends (e.g., in snowpack duration or growing season length). We describe the use of Moderate Resolution Imaging Spectroradiometer (MODIS) data from Aqua and Terra satellites to monitor lake ice seasonal dynamics in southwest Alaska. This paper focuses on the lake ice metrics, including the timing and duration of ice formation and break-up on large lakes as manually interpreted from Rapidfire MODIS images. The moderate spatial resolution (250–1000 m) and high temporal resolution provided by MODIS enables frequent observations of a region characterized by a rapidly changing landscape, complex climatic regime, frequent cloud cover, and little infrastructure to support ground-based measurements. The National Park Service (NPS) is also monitoring the landscape dynamics of snow and growing seasons for the study area using standard MODIS snow and NDVI products. Summary metrics for snow cover and vegetation phenology (start and end of season) were also derived using standard MODIS products for snow and NDVI (Reed et al, in press). We examined variation in each metric across years (2001-2007) and the relationships among metrics. Background Increasing temperatures projected for the northern high latitudes over the next century are expected to influence a number of seasonal events including lake ice formation and break-up, snowpack formation, and onset of growing season. Milder winters have resulted in later freeze-up dates, earlier break-up dates, or both for lakes in the northern United States and Canada (Magnuson et al., 2000) and are expected to affect the frequency and severity of ice dams, floods, and low flows in the Arctic. In southwest Alaska, the seasonality of snowpack, lake ice, and vegetation dynamics are expected to have wide- reaching effects. The climate is influenced by complex interactions of several forcing agents, all functioning at different temporal scales: the El Niño and La Niña Southern Oscillation (one-two years), the Pacific Decadal Oscillation (20-30 years) and the Pacific/North American circulation pattern (days to weeks), as well as local forcings resulting from topography (Papineau 2001). These climatic factors influence the timing of freeze-thaw events, lake ice thickness, and surface and groundwater hydrology in the region. Such climate-driven effects on habitat and forage may affect wildlife populations, including caribou, moose, wolves, and a number of other predator and prey species. The presence or absence of lake ice and snow also affects winter access to subsistence activities by rural residents who depend on these resources (e.g., ice fishing, hunting, trapping, firewood collection) (Gaul 2007). Accurate measurements of regional-scale lake ice dynamics, vegetation, and snowpack are needed to improve our understanding of the long-term effects of climate on southwest Alaska ecosystems. The National Park Service’s Inventory and Monitoring (I&M) Program has begun to monitor these variables as a means of characterizing short- and long-term variation in seasonality. Moderate resolution remote sensing data provide a means for monitoring trends in snowpack, lake ice, and vegetation dynamics in this otherwise remote and inaccessible region. The high temporal resolution of MODIS data makes them especially well-suited to capture variation in the timing of seasonal events across years. Lake Ice Formation and Break-up Process Water density is greatest at 4oC. In the generalized ice formation process, early season autumn snowfall lowers water temperature as snow melts into open water. Surface water cools to 4oC from lowering air temperature and snow. The denser water sinks and the lighter surface water cools until the entire lake mass reaches 4oC. Without further mixing from wind, a lighter layer of water forms on the surface and further cools to 0oC, when a thin layer of skim ice forms (Jeffries et al., 2005). Often, the entire surface of a lake will freeze over within a few hours on a still cold night. The ice layer thickens as additional water freezes to the bottom. Maximum ice thickness varies each winter depending on air temperatures, snow cover and duration of cold weather. Many winters in southwestern Alaska experience mid-winter thaw events as the jet stream moves to the eastern Gulf of Alaska, allowing a strong stream of warm moist air (Chinook storms) to flow north and hit the southern coast of Alaska. This sudden influx of warm air, rain and wind removes the insulating snow cover and the ice surface is flooded with several inches of water. The return of the Arctic high pressure system and cold temperatures refreeze the lake surfaces. This ice cover generally lasts until breakup. Spring breakup of lake ice begins as the days become longer and warmer. Ice decays when the ice becomes isothermal at 0oC and the top and bottom of the ice layer melt simultaneously. Sometimes melting occurs inside the ice layer along the vertical ice crystals, forming columnular or needle ice which rapidly fractures apart, speeding breakup. Thermal absorption from open water, light winds and gentle waves accelerate the melting process. As with freeze-up, breakup can be very rapid, with even large lakes becoming ice free within a few days. Once ice free, lake water gradually warms throughout the summer, reaching 15oC at the surface during warm years. However, Pecora 17 – The Future of Land Imaging…Going Operational November 18 – 20, 2008 Denver, Colorado water at 50m deep in Lake Clark barely warms to 5oC (NPS unpub data) before the advent of fall storms and the cycle of cooling and ice formation continues. METHODS Study Area The study area (Fig. 1) comprises nearly 20 million ha of land between about 56–62° N latitude and 148–160° W longitude in southwest Alaska. It includes the Southwest Alaska Network (SWAN), one of 32 networks in the U.S. National Park Service’s (NPS) Inventory and Monitoring Program (Fancy et al., 2008), which consists of five National Park Service units (Alagnak Wild River, Aniakchak National Monument & Preserve, Katmai National Park & Preserve, Kenai Fjords National Park, Lake Clark National Park & Preserve). This study was initiated as part of the NPS Vital Signs monitoring effort. Southwestern Alaska is characterized by diverse terrain, ranging from gently rolling coastal lowlands to steep, dissected mountain ranges and glaciated valleys. Elevation ranges from 0 to 3100 m. Mean annual precipitation ranges from 400–600 mm in the western interior to 3000–4000 mm at higher elevations and along the eastern coastline of the Cook Inlet Basin (Davey et al., 2007). Mean annual temperature ranges from –8 °C in the western interior to 4 °C in the coastal lowlands, with the growing season generally limited to May–October at lower elevations. Winter temperatures at lower elevations in the region fluctuate around 0 °C.